Strain imaging has been used in ultrasound medical imaging to differentiate between hard tissue and soft tissue. For example, since tumors are generally harder than normal tissues, strain imaging may be used evaluate solid breast masses. Strain images are created by comparing echo data obtained before and after a slight compression of the tissue. The results of the comparison are displayed as an image on which the hard areas appear dark and soft areas appear bright. Other black-and-white and other color scale may be employed for display. Typically strain imaging is accomplished by comparing the hard and soft tissue in a region of interest on a pixel by pixel basis using conventional ultrasound equipment.
Typically strain images are made from strain measure point by point, pixel by pixel, before and after compression. However, there are several problems with this type of method for quantifying the strain. First, there are artifacts that can be generated based on the probe usage over several points. Second, the system is time-consuming and tedious. Thirdly, other areas can distort the measured strain due to shadows, cavities and other areas of anomalies within the area being imaged.
Accordingly, what is desired is a system to more accurately and quickly quantify compression-induced strain the traditional brightness mode (B-mode) images. The present invention addresses such a need.
In recent years, several strain-imaging techniques have been proposed and developed by various research groups. In order to increase the spatial resolution for strain imaging, the adjacent local blocks, which are typically used to determine their displacements should be close enough. But there are technical difficulties for accurately determining the difference of displacements over these local blocks and generate the poor signal to noise ratio (SNR) for the strain images and therefore quantifying the strain measurements. Additionally, the levels of echo signals (which are related to the back-scatter coefficients of insonifying tissue) from different types of tissues may be quite different, such as the echo signals from healthy breast tissue could be significantly different from the echo signals from breast cancer. These differences will cause additional errors for our motion estimation.
Accordingly, what is needed is a system and method for overcoming these problems. The present invention addresses such a need.